Simulated Annealing for Materialized View Selection in Data Warehousing Environment

View/ Open
Author(s)
Derakhshan, Roozbeh
Dehne, Frank
Korn, Othmar
Stantic, Bela
Griffith University Author(s)
Year published
2006
Metadata
Show full item recordAbstract
In order to facilitate query processing, the information contained in data warehouses is typically stored as a set of materialized views. Deciding which views to materialize presents a considerable challenge. The task is to select from a very large search space a set of views that minimizes view maintenance and query processing costs. Heuristic methods have been employed to find near optimal solutions and recent genetic algorithms have significantly improved the quality of the obtained solutions. In this paper we introduce a new approach for materialized view selection that is based on Simulated Annealing in conjunction ...
View more >In order to facilitate query processing, the information contained in data warehouses is typically stored as a set of materialized views. Deciding which views to materialize presents a considerable challenge. The task is to select from a very large search space a set of views that minimizes view maintenance and query processing costs. Heuristic methods have been employed to find near optimal solutions and recent genetic algorithms have significantly improved the quality of the obtained solutions. In this paper we introduce a new approach for materialized view selection that is based on Simulated Annealing in conjunction with the use of a Multiple View Processing Plan (MVPP). Our experiments show that our new method provides a further significant improvement in the quality of the obtained set of materialized views, leading to a further significant improvement in query processing time and view maintenance costs for data warehousing systems.
View less >
View more >In order to facilitate query processing, the information contained in data warehouses is typically stored as a set of materialized views. Deciding which views to materialize presents a considerable challenge. The task is to select from a very large search space a set of views that minimizes view maintenance and query processing costs. Heuristic methods have been employed to find near optimal solutions and recent genetic algorithms have significantly improved the quality of the obtained solutions. In this paper we introduce a new approach for materialized view selection that is based on Simulated Annealing in conjunction with the use of a Multiple View Processing Plan (MVPP). Our experiments show that our new method provides a further significant improvement in the quality of the obtained set of materialized views, leading to a further significant improvement in query processing time and view maintenance costs for data warehousing systems.
View less >
Conference Title
PROCEEDINGS OF THE IASTED INTERNATIONAL CONFERENCE ON DATABASES AND APPLICATIONS
Publisher URI
Copyright Statement
© 2006 IASTED and ACTA Press. This is the author-manuscript version of this paper. Use hypertext link for access to the publisher's website.
Subject
History, heritage and archaeology